Radar high resolution range profile target recognition based on time series forest

Abstract

In order to improve the recognition accuracy of radar targets and the recognition performance under incomplete angular domain data, a high resolution range profile (HRRP) recognition algorithm based on time series forest is proposed. The basic principle of time series forest algorithm and the basic steps of HRRP target recognition are introduced in detail. The experimental results of measured HRRP data show that compared with k-nearest neighbors(KNN), support vector machine(SVM), random forest(RF), convolutional neural network(CNN), long short-term memory(LSTM) and other classical target recognition algorithms, the proposed algorithm has better recognition performance and better angular domain promotion ability. Under the condition of training only 1/2 and 1/3 angular domain data, the average recognition rate of the full angular domain data is better than 85%, which is an average increase of 5.2% compared with the above method.

Keywords

• ratr|hrrp|tsf|incomplete angular domain